Binary Representation in Gene Expression Programming: Towards a Better Scalability
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{conf/isda/Moreno-TorresLG09,
-
title = "Binary Representation in Gene Expression Programming:
Towards a Better Scalability",
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author = "Jose Garcia Moreno-Torres and Xavier Llora and
David E. Goldberg",
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booktitle = "Ninth International Conference on Intelligent Systems
Design and Applications, ISDA '09",
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year = "2009",
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month = "30 " # nov # "-2 " # dec,
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pages = "1441--1444",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/isda/isda2009.html#Moreno-TorresLG09",
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keywords = "genetic algorithms, genetic programming, gene
expression programming, machine learning, classifier
systems",
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DOI = "doi:10.1109/ISDA.2009.33",
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publisher = "IEEE Computer Society",
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abstract = "One of the main problems that arises when using gene
expression programming (GEP) conditions in learning
classifier systems is the increasing number of symbols
present as the problem size grows. When doing
model-building LCS, this issue limits the scalability
of such a technique, due to the cost required. This
paper proposes a binary representation of GEP
chromosomes to palliate the computation requirements
needed. A theoretical reasoning behind the proposed
representation is provided, along with empirical
validation.",
-
notes = "Also known as \cite{5363972}",
- }
Genetic Programming entries for
Jose Garcia Moreno-Torres
Xavier Llora
David E Goldberg
Citations